Mixture models for quantitative HIV RNA data

Research output: Contribution to journalArticle

Abstract

Clinical investigators are increasing their use of quantitative determinations of HIV viral load in their study populations. The distributions of these measures may be highly skewed, left-censored, and with an extra spike below the detection limit of the assay. We recommend use of a mixture model in this situation, with two sets of explanatory covariates. We extend this model to incorporate multiple measures across time, and to employ shared parameters as a way of increasing model efficiency and parsimony. Data from a cohort of HIV-infected men are used to illustrate these features, and simulations are performed to assess the utility of shared parameters.

Original languageEnglish (US)
Pages (from-to)317-325
Number of pages9
JournalStatistical Methods in Medical Research
Volume11
Issue number4
DOIs
StatePublished - Aug 2002

Fingerprint

Mixture Model
HIV
RNA
Parsimony
Detection Limit
Viral Load
Spike
Limit of Detection
Covariates
Research Personnel
Model
Population
Simulation

ASJC Scopus subject areas

  • Epidemiology
  • Nursing(all)
  • Health Information Management

Cite this

Mixture models for quantitative HIV RNA data. / Moulton, Lawrence Hale; Curriero, Frank C; Barroso, Paulo F.

In: Statistical Methods in Medical Research, Vol. 11, No. 4, 08.2002, p. 317-325.

Research output: Contribution to journalArticle

@article{5929184715b543e181d254ece0b049fe,
title = "Mixture models for quantitative HIV RNA data",
abstract = "Clinical investigators are increasing their use of quantitative determinations of HIV viral load in their study populations. The distributions of these measures may be highly skewed, left-censored, and with an extra spike below the detection limit of the assay. We recommend use of a mixture model in this situation, with two sets of explanatory covariates. We extend this model to incorporate multiple measures across time, and to employ shared parameters as a way of increasing model efficiency and parsimony. Data from a cohort of HIV-infected men are used to illustrate these features, and simulations are performed to assess the utility of shared parameters.",
author = "Moulton, {Lawrence Hale} and Curriero, {Frank C} and Barroso, {Paulo F.}",
year = "2002",
month = "8",
doi = "10.1191/0962280202sm292ra",
language = "English (US)",
volume = "11",
pages = "317--325",
journal = "Statistical Methods in Medical Research",
issn = "0962-2802",
publisher = "SAGE Publications Ltd",
number = "4",

}

TY - JOUR

T1 - Mixture models for quantitative HIV RNA data

AU - Moulton, Lawrence Hale

AU - Curriero, Frank C

AU - Barroso, Paulo F.

PY - 2002/8

Y1 - 2002/8

N2 - Clinical investigators are increasing their use of quantitative determinations of HIV viral load in their study populations. The distributions of these measures may be highly skewed, left-censored, and with an extra spike below the detection limit of the assay. We recommend use of a mixture model in this situation, with two sets of explanatory covariates. We extend this model to incorporate multiple measures across time, and to employ shared parameters as a way of increasing model efficiency and parsimony. Data from a cohort of HIV-infected men are used to illustrate these features, and simulations are performed to assess the utility of shared parameters.

AB - Clinical investigators are increasing their use of quantitative determinations of HIV viral load in their study populations. The distributions of these measures may be highly skewed, left-censored, and with an extra spike below the detection limit of the assay. We recommend use of a mixture model in this situation, with two sets of explanatory covariates. We extend this model to incorporate multiple measures across time, and to employ shared parameters as a way of increasing model efficiency and parsimony. Data from a cohort of HIV-infected men are used to illustrate these features, and simulations are performed to assess the utility of shared parameters.

UR - http://www.scopus.com/inward/record.url?scp=0036667563&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0036667563&partnerID=8YFLogxK

U2 - 10.1191/0962280202sm292ra

DO - 10.1191/0962280202sm292ra

M3 - Article

C2 - 12197299

AN - SCOPUS:0036667563

VL - 11

SP - 317

EP - 325

JO - Statistical Methods in Medical Research

JF - Statistical Methods in Medical Research

SN - 0962-2802

IS - 4

ER -